Routine Activity Theory
Abstract and Keywords
“Opportunity makes the thief” is a saying that emphasizes one thing: crime requires not only the presence of a willing offender but also an opportunity. Based on this notion, even the most motivated offender cannot commit a crime unless he sees an opportunity to do so. The concept of opportunity is therefore important in explaining why crime incidents occur across persons and their property. Routine activity theory, proposed by Lawrence E. Cohen and Marcus Felson, offers an account of how opportunities for crime arise through the day-to-day activities carried out by individuals to meet their needs. Individuals have different routines of life—traveling to and from work, going to school or attending religious functions, shopping, recreating, communicating via various electronic technologies, etc.—and these variations determine the likelihood of when and where a crime will be committed and who or what is the victim. This article examines theoretical and methodological issues relevant to testing routine activity theory and reviews major empirical findings from the extant literature.
The saying, “Opportunity makes the thief,” suggests that crime requires more than just the presence of a willing offender; it requires an opportunity. Even the most motivated offender cannot commit a crime unless an opportunity to carry out illegal activity presents itself. Notably, numerous opportunities for crime exist daily, yet they are not ubiquitous. Rather, opportunities are socially patterned and not evenly distributed across time, across physical or cyberspace, and across persons and their property. Given these observations, it is apparent that the concept of opportunity is central to explaining the occurrence of crime incidents across persons and their property.
Routine activity theory, as proposed by Cohen and Felson (1979), explains how opportunities for crime are produced through the day-to-day activities that individuals engage in to meet their needs. Variations in individuals’ routines of life—traveling to and from work, school, or religious institutions; shopping; recreating; communicating via various electronic technologies; and so forth—determine the likelihood of when and where criminal events occur and who or what is the victim.
Despite a growing body of research testing routine activity theory, few reviews of the empirical evidence exist (for exceptions, see Pratt and Cullen 2005; Spano and Freilich 2009). Most published research is limited because it either tests partially one or a few of the perspective’s theoretical concepts, or because it examines a single type of victimization. These limitations preclude assessing the relative importance of routine activity compared to other theories and preclude isolating specific routines that consistently predict victimization.
(p. 514) This chapter presents a critical discussion of theoretical and methodological issues relevant to testing routine activity theory and reviews the extant literature’s major empirical findings. In sections I and II, we consider the theory’s main propositions and distinctive assumptions compared to mainstream criminological theories. Section III reviews elaborations of the theory. This discussion is followed in section IV by an appraisal of the theory’s major measurement issues and methodological challenges. Section V presents an overview of the empirical validity of the theory, including a discussion of studies at various levels of analysis and multiple types of crime. The chapter concludes in section VI by highlighting the following major points:
• Despite the simplicity of its theoretical propositions, research testing the validity of routine activity theory has important methodological caveats. Many studies rely on proxy measures of key concepts and fail to account for crime-specific dynamics, which undermines theory falsification and precludes an understanding of the causal mechanisms of victimization.
• The accumulated evidence offers moderate support for routine activity theory as applied to property victimization. Among the best predictors are home occupancy, out-of-household leisure activity, possessing valuables, safety precautions, and target hardening measures.
• There is inconclusive evidence regarding the validity of routine activity theory for violent victimization. Participation in deviant lifestyles as well as drug and alcohol use are consistent predictors, but other high-exposure lifestyles have no effects on the risk of violent victimization.
• Routine activity theory has been supported in studies of criminal offending. Unsupervised, unstructured activities appear to be risk factors for criminal behavior.
• The evidence from macro-level studies is mixed. Most support comes from studies at the lowest levels of aggregation, but studies of standard metropolitan statistical areas (SMSAs) and cities show few significant effects.
• Multilevel studies of criminal opportunity offer moderate support for the theory, showing significant main and interaction effects between individual predictors and neighborhood context.
I. Theoretical Foundations
Routine activity theory provides an explanation for crime patterns through the application of ecological theory. Cohen and Felson (1979) drew from Amos Hawley’s (1950) work on human ecology, which emphasizes the concepts of codependence and sustenance. For Hawley, communities are organized around means of sustenance from the environment. The concept of symbiosis reflects mutual dependence among functionally dissimilar organisms, and commensalism captures relations among functionally similar (p. 515) ones. Predatory behavior, including crime, is a form of symbiosis. A first contribution of Hawley’s work to routine activity theory is to demonstrate that illegal activities must feed upon legal activities. If legal and illegal activities are intertwined, it follows that patterns of conventional activities will be important to predict victimization patterns (Felson and Cohen 1980). Herein lies the paradox posed by routine activity theory: predatory crime is a natural result of legal activities.
Cohen and Felson (1979, p. 593) defined routine activities as “recurrent and prevalent activities which provide for basic population and individual needs.” Hawley called attention to the temporal interdependence between community structure and crime, and three relevant components of the temporal organization of routines: the regular periodicity with which events occur (rhythm), the number of events occurring per unit of time (tempo), and the coordination across various activities (timing). To the extent that the rhythm, tempo, and timing of activities are predictable, they become habitual daily patterns. A second contribution of Hawley’s ecological approach is an emphasis on the spatio-temporal structure of routines. Routine activity theory proposes that conventional routines influence the location, time, and type of crime.
Implicit in this discussion is that crime incidents are not random occurrences but rather structured phenomena. Cohen and Felson (1979) argued that crime is the result of the convergence in time and space of three necessary elements: (1) motivated offenders, (2) suitable targets, and (3) the absence of capable guardians who can prevent the crime. Together, these elements characterize the criminal opportunity; all three elements must converge in time and space for a crime to occur.
Cohen and Felson proposed their theory as a possible explanation for the increase in U.S crime rates since the 1960s. They hypothesized that changes in routine activities at the aggregate level would be positively associated with changes in crime rates. They calculated a household activity ratio,1 a structural indicator of the dispersion of activities away from the household and the likelihood of owning attractive durable goods. They examined annual rates of homicide, forcible rape, aggravated assault, robbery, and burglary between 1947 and 1974 as a function of this ratio. Controlling for age structure and unemployment rate, the household ratio was a positive significant predictor of each type of crime. Their study provided the first empirical evidence supporting routine activity theory’s ability to explain crime rates.
II. Distinctions from Mainstream Criminological Theories
Routine activity theory can be distinguished from mainstream criminological theories on two fundamental aspects. First, most criminological theories have the offender as the unit of analysis and downplay the importance of the very event in which the offender breaks the law—the crime incident. Within the routine activity approach, (p. 516) the offender is not a sufficient element for a crime to occur, but one of three necessary elements. Hence, the crime incident is the unit of analysis, which requires information not only about the offender but also about the role played by targets and guardians.
A second distinction is that routine activity theory does not identify the sources of criminal motivation or explain why individuals vary in their propensity to offend. Cohen and Felson (1979) did not include any measure of offender motivation and argued that spatio-temporal variations in aggregate-level routine activities affect crime rates, independent of changes in the causes of criminal predispositions. This is not to imply that individual differences in criminal inclinations do not exist, or that criminal motivation is universal, but routine activity theory does not explain the sources of these differences (Wilcox, Land, and Hunt 2003).
III. Expansions of Routine Activity Theory
A notable expansion is the formal application of routine activity theory to the individual level. Cohen, Kluegel, and Land (1981) proposed an opportunity model of predatory victimization that integrates routine activity with the lifestyle-exposure perspective developed by Hindelang, Gottfredson, and Garofalo (1978). Although these two theories have substantial overlap, the lifestyle-exposure perspective conceives victimization as a function of the differential exposure to high-risk places, times, and persons that is characteristic of some lifestyles. Lifestyles are, in turn, affected by sociocultural roles and structural constraints. Hindelang and colleagues (1978) argue that differences in the risk of victimization by gender, age, income, and other demographic characteristics are attributable to lifestyles that differentially expose these groups to risky environments.
Based on these observations and Cohen and Felson’s macro-level approach, Cohen and colleagues (1981) derived an integrated approach to explain individual victimization. According to these scholars, criminal opportunities are a function of four components: exposure and proximity to motivated offenders, target attractiveness, and guardianship. Variations in criminal opportunities, in turn, relate to variations in the risk of victimization. Studies that conceive the criminal opportunity as comprised of these four factors are tests of the lifestyle-routine activity approach.
First, Cohen and colleagues defined the concept of proximity as “the physical distance between the areas where potential targets of crime reside and where relatively large populations of potential offenders are found” (1981, p. 507). The lifestyle-routine activity approach specifies a positive relationship between proximity and victimization risk. For example, people who live or spend large amounts of time in high-crime areas have higher risks of encountering potential offenders, thereby increasing their risk of victimization.
Second, exposure refers to the visibility and accessibility of possible targets within risky environments. Unlike the concept of proximity, which emphasizes the contact (p. 517) with offenders, exposure refers to the contact with risky or vulnerable situations at particular times, and with particular kinds of persons (Meier and Miethe 1993). A positive relationship between exposure and victimization risk is expected; individuals who place themselves in risky environments are more likely to become crime victims. For example, drinking alcohol in a sports bar with fans from a rival team increases a person’s risk of personal victimization during and immediately after the game.
Third, target attractiveness is similar to target suitability as described by Cohen and Felson (1979), although much narrower.2 Cohen, Kluegel, and Land (1981) contended that two characteristics make a target attractive: material and/or symbolic desirability to potential offenders (value), and inability to pose resistance/portability (inertia). In contrast, Cohen and Felson (1979) proposed four characteristics of a suitable target, or VIVA: Value, Inertia, Visibility, and Accessibility. More attractive targets are expected to be at higher risk of victimization, such as a person displaying a large sum of cash in public.
Fourth, guardianship refers to the ability of persons or objects to successfully prevent crime. Social guardianship includes protection by family or social networks such as friends, coworkers, and neighbors. Physical guardianship refers to target-hardening tools. Contrary to the other three criminal opportunity elements, which are construed as risk factors, guardianship is a protective factor. Hence, targets with lower levels of guardianship are assumed to have a higher risk of victimization.
Scholars expanded these theoretical foundations in two fundamental directions. First, the original conceptualization of an attractive target fails to account for the offender’s view and offenders not being equally drawn to all types of victims (Finkelhor and Asdigian 1996). Similarly, the offender’s assessment of target suitability includes issues such as the disposal of stolen goods, which are beyond the scope of the original concept (Clarke 1999).
New conceptualizations of target attractiveness have been proposed to overcome these limitations. First, Finkelhor and Asdigian (1996) proposed that the victimization risk is affected by three target features that reflect the offender’s predispositions, proclivities, and reactivities: target vulnerability, target gratifiability, and target antagonism. Their most unique contribution to routine activity theory is with respect to target antagonism, defined as those target characteristics that arouse the offender’s anger or destructive impulses. They found evidence that target attractiveness predicted the risk of nonfamily and sexual assault among youths. Second, Clarke (1999) proposed that target suitability is better represented by CRAVED: Concealable, Removable, Available, Valuable, Enjoyable, and Disposable. He presented evidence showing that target suitability predicts victimization, based on CRAVED characteristics, but this varies by type of crime.
A second expansion involves the concept of guardianship. Wilcox, Madensen, and Tillyer (2007) drew from environmental criminology and multicontextual criminal opportunity theory to propose four types of guardianship at the individual and aggregate levels: physical, personal, social, and natural. Individual-level guardianship refers to social ties and interpersonal control, whereas aggregate-level guardianship refers to the “collective degree to which individuals or objects in a bounded locale (p. 518) possess qualities related to social ties and social control” (2007, p. 773). Wilcox and colleagues used both individual- and neighborhood-level measures of target hardening, homeowner occupancy, neighbor-provided surveillance and informal control, and defensible space. They found significant interactions between these two levels of guardianship. For example, their findings revealed that the effect of individual-level target hardening in reducing the risk of burglary was accentuated in neighborhoods with a higher level of defensible space. These findings suggest that guardianship should be conceived within a broader scope than Cohen and Felson’s original thesis.
More recently, researchers have extended the application of routine activity theory beyond the traditional place-based approach. Criticisms of the theory’s adequacy to explain Internet fraud, cyberstalking, and other forms of cybervictimization highlight the possibility that these offenses may occur without an actual physical interaction between the parties or without a synchronized timing in victim-offender activities. To overcome this theoretical and empirical gap, Reyns, Henson and Fisher (2011) proposed an adapted lifestyle-routine activity theory. Whereas Cohen and Felson (1979) specified the convergence in space and time between victims and offenders as a sine qua non for criminal opportunities, Reyns and colleagues propose that such convergence is not necessary in cyberspace. Because cyberspace takes the place of physical space in the adaptation conceived by Reyns et al., the physical encounter between victims and offenders is not a necessary condition for victimization. Instead, what is necessary is an interaction between victim and offender through a system or network, such as a telecommunications system or a mail delivery system. The authors also adapt the concept of time to cyberspace, arguing that offenders and victims do not have to interact with each other instantanously for a victimization to occur. Time represents the setting in motion of the offenders’ behavior, but the actual victimization does not occur until the victim experiences the intended harm (e.g., a harassing e-mail). The authors tested their adapted “cyberlifestyle-routine activity theory” with a sample of college students. Their results showed that online measures of each of the key concepts—proximity to motivated offenders, lack of guardianship, target attractiveness, and exposure to likely offenders—were strong predictors of different types of cyberspace victimization, including cyberstalking, harassment, and unwanted sexual advances. These findings highlight the general nature of routine activity theory and show how it can be extended to various types of crime.
IV. Measurement of Key Theoretical Concepts
The parsimonious nature of routine activity theory has allowed researchers to test its utility across different types of violent and property victimization (Fisher and Wilkes 2003; Tseloni, Wittebrood, Farrell, and Pease 2004; Burrow and (p. 519) Apel 2008), fraud (Pratt, Holtfreter, and Reisig 2010), stalking (Mustaine and Tewksbury 1999; Fisher, Cullen, and Turner 2002), and cyberspace victimization (Reyns, Henson, and Fisher 2011). Its application to a wide range of victimization allows for an examination of the measures used to operationalize key concepts. As a prelude to our review of the empirical evidence, we discuss methodological challenges to measuring the four key concepts in the following subsections.
A. Proximity to Motivated Offenders
Proximity to motivated offenders refers to the physical distance between targets and areas where large numbers of potential offenders concentrate (Meier and Miethe 1993). Measuring this concept requires information about the location of victims and likely offenders. Given the difficulties inherent in measuring the presence of motivated offenders, most studies have used indirect measures. These studies assume that offenders select targets that are in close proximity to their residence; as a result, living in a high-crime area implies close proximity to likely offenders. Indicators include victim’s place of residence, neighborhood unemployment rates, and crime rates (Cohen and Cantor 1981; Sampson and Wooldredge 1987). In the case of place of residence, for example, researchers have presumed that those living in urban areas are in closer proximity to motivated offenders than individuals living in suburban or rural areas (Kennedy and Forde 1990; Tseloni et al. 2004).
Other studies rely on the respondents’ perceptions of crime and disorder in their neighborhood, or perceived dangerousness in the workplace, to measure proximity (Lynch 1987; Massey, Krohn, and Bonati 1989; Wooldredge, Cullen, and Latessa 1992). This approach assumes that individuals can reliably assess the presence of motivated offenders in their surroundings. A possible criticism is that the respondents’ perception of their neighborhood as dangerous may also be dependent on prior victimization experiences. Insofar as individuals who have been victimized tend to judge their environment as less safe, cross-sectional studies cannot determine whether a negative link between perceived neighborhood safety and victimization is due to proximity, as the theory would anticipate, or is simply an artifact of prior victimization.
Miethe and Meier’s (1990) study is among the few investigations to employ multiple measures of proximity. Their unique contribution is that they employed a direct measure of proximity—the self-reported rate of offending—along with the victim’s place of residence and perceived neighborhood safety, to predict an individual’s risks of burglary, personal theft, and personal violence. The results showed only small inter-item correlations among the measures, suggesting that they capture separate dimensions of proximity. Further, these results demonstrated the importance of using multiple measures of proximity. Despite these measurement advancements, few studies include any indicator of proximity, making it one of the least tested concepts of routine activity theory.
(p. 520) B. Exposure to Motivated Offenders
The concept of exposure to motivated offenders reflects the accessibility and visibility of targets located in risky environments (Cohen, Kluegel, and Land 1981). Similar to proximity, this concept has been measured using indirect and direct indicators. Research has transitioned from the use of proxies to the use of more refined measures. Early studies relied on sociodemographic variables—marital status and occupation—to capture levels of nonhousehold activity and measure lifestyles (Cohen and Cantor 1981; Cohen, Kluegel, and Land 1981).
In light of Mustaine and Tewksbury’s (1998) call for using more refined measures, a limited number of studies incorporate direct indicators, including measures of how and where the respondents spend their time (Kennedy and Forde 1990; Mustaine and Tewksbury 1998). Studies of personal victimization use as indicators of exposure the frequency of nighttime activity, type of leisure activities, participation in extracurricular activities, drinking habits, and participation in deviant lifestyles (Sampson and Lauritsen 1990; Wilcox Rountree, Land, and Miethe 1994; Fisher et al. 1998; Messner et al. 2007; Wilcox, Tillyer, and Fisher 2009). Direct measures of exposure in property victimization studies include the number of hours a household is unoccupied, the visibility of the property, access routes, and location relative to other dwellings (Wilcox Rountree and Land 1996; Tseloni et al. 2004; Coupe and Blake 2006).
C. Target Attractiveness
The concept of target attractiveness reflects symbolic or economic value, an individual’s inertia to attacks, and the ease of removal of a potential victim’s property (Meier and Miethe 1993). Cohen, Kluegel, and Land (1981) noted that target attractiveness varies depending on whether the crime is instrumental, where the criminal act is a means for achieving a tangible goal or desired outcome (e.g., burglary), or expressive, where the act of the crime is an end in itself because it brings about an intrinsic reward (e.g., physical assault). Conceivably, economic value is a salient feature of an attractive target for an instrumental crime, but is less so for an expressive crime.
Most researchers measure a target’s attractiveness in terms of its economic value. Research on personal larceny, robbery, or theft victimization uses indicators such as family income, ownership of expensive items, jewelry worn in public, and cash handled or carried openly (Lynch 1987; Miethe, Stafford, and Long 1987; Sampson and Wooldredge 1987; Messner et al. 2007). Studies of burglary, on the other hand, employ measures such as housing value, household socioeconomic status, or ownership of portable items (Miethe and McDowall 1993; Zhang, Messner, and Liu 2007). Operationalizing target attractiveness only as economic value is problematic, however, given that targets may be attractive for other reasons, particularly in expressive types of victimization. Further, inertia and portability are also dimensions of target attractiveness, yet few studies include measures of these dimensions (for exception, see Pires and Clarke forthcoming).
(p. 521) Operationalizing target attractiveness as it applies to expressive crimes has challenged researchers. Although it can be argued that assault and robbery could be financially motivated, nonpecuniary rewards from victimization are equally appealing to offenders. Most studies, however, fail to capture this aspect. Finkelhor and Asdigian (1996) suggested that it may be more appropriate to refer to target congruence and to include indicators of vulnerability, gratifiability, and antagonism. Studies operationalize these concepts using physical stature, physical impairment or disability, school fighting, and impulsivity (Finkelhor and Asdigian 1996; Burrow and Apel 2008; Wilcox, Tillyer, and Fisher 2009). In sexual victimization studies, target attractiveness is operationalized using drug and alcohol consumption, assuming that these behaviors reduce the target’s ability to take self-protective actions (Mustaine and Tewksbury 2002; Cass 2007). For stalking victimization, an attractive target may be someone who regularly dates or has been involved in intimate relationships, because the offender is likely a former partner who knows the victim’s lifestyles and routines (Fisher, Cullen, and Turner 2002).
Another limitation of target attractiveness indicators, particularly those reflecting economic value, is that they imply that offenders have information about the target. Prior studies hypothesize that households containing valuable items—laptop, iPad, DVD, TV—have a high risk of burglary, given their increased attractiveness to offenders (Sampson and Wooldredge 1987). It is possible that offenders do not know in advance whether a selected residence contains such items. Similarly, people who carry cash in public may cue would-be offenders to victimize them, but possibly what makes them attractive targets is not that they carry cash but that they do not conceal it.
The concept of guardianship refers to the supervision of persons or objects that can prevent crime from occurring (Cohen and Felson 1979; Felson and Cohen, 1980). Similar to exposure, the measurement of guardianship has improved over time. Thus, to measure social guardianship, studies examine the number of adults living at home, whether neighbors or friends watch the property, whether the resident participates in neighborhood watch, and whether the resident lives alone (Miethe and McDowall 1993; Tseloni et al. 2004; Zhang, Messner, and Liu 2007). In the case of delinquency, studies use measures of the degree of parental attachment to capture the concept of social guardianship (Schreck, Stewart, and Fisher 2006). Physical guardianship is operationalized with various target hardening indicators, such as door locks or a burglar alarm in homes, the resident carrying a weapon, the resident participating in self-protection training, and the resident owning a dog (Wilcox Rountree, Land and Miethe 1994; Fisher et al. 1998; Mustaine and Tewksbury 1998; Outlaw, Ruback, and Britt 2002). One criticism of the use of target hardening measures suggests that they reflect target suitability, a concept that is distinct from capable guardianship. Hollis-Peel and colleagues (2011) argued that individuals exercise guardianship when they watch over a potential target to deter potential offenders, while target hardening refers to decreasing the suitability of a target by making actual changes so that the target is less attractive to potential offenders.
(p. 522) Researchers have incorporated measures beyond home occupancy, including components of natural guardianship, such as defensible space (Wilcox, Madensen, and Tillyer 2007). Reynald (2009) has argued for the measurement of actual guardianship intensity, which includes three elements: a guardian’s availability, capability, and willingness to intervene. She showed that crime varies inversely across levels of guardianship intensity. As these studies illustrate, the measurement of guardianship is superior to other concepts, perhaps due to greater use of refined indicators.
E. Overview of Limitations in the Measurement of the Key Concepts
Notwithstanding improvements in the measurement of the key concepts of proximity, exposure, target attractiveness, and guardianship, routine activity theory research suffers from three main limitations: reliance on proxy measures, theoretical indeterminacy among concepts, and use of broadly defined measures that fail to capture crime-specific dynamics.
First, the use of proxy measures is problematic because in the absence of direct measures of lifestyles-routines, it is not only difficult to falsify the theory but is impossible to isolate specific routines-lifestyles most associated with certain types of victimization. Observed relationships may be consistent with the predictions of alternative theories. For instance, macro-level research often has used unemployment as an indicator of motivated offenders, but this variable is “claimed” by other macro-level theories, so that a positive link between unemployment and crime rates has various interpretations. Such a finding may support economic/resource deprivation theory or even social disorganization theory (Pratt and Cullen 2005). Based on proxy measures only, it is impossible to disentangle these effects because the same finding can be explained under competing theories.
Second, Meier and Miethe (1993) discussed the issue of theoretical indeterminacy—the idea that some indicators may represent more than one underlying key concept (see also Spano and Freilich 2009). The conceptual ambiguity of a routine activity indicator is compounded when researchers use proxy measures of concepts. For example, some studies use family income to capture guardianship, with wealthier families being able to afford protective measures (Cohen, Kluegel, and Land 1981). However, family income may be also indicative of exposure because those with higher incomes can afford to often attend entertainment outside the home. In the former example, family income is a protective factor whereas in the latter it is a risk factor. The same measure can imply very different causal mechanisms, with relationships to victimization risk in opposite directions, depending on how target attractiveness is conceptualized. The challenge is to develop measures that are specific enough to differentiate theoretical concepts so that causal mechanisms can be identified.
Even when using refined measures, there may be alternative theoretical interpretations. Whereas some studies claim that alcohol and drug use are indicators of target attractiveness because they reduce an individual’s ability to fend off the perpetrator (p. 523) (Mustaine and Tewksbury 2002; Spano and Nagy 2005), others interpret these as indicators of exposure to motivated offenders (Sampson and Lauritsen 1990; Spano and Nagy 2005), or as indicators of reduced guardianship (Gover 2004). These examples illustrate the lack of consensus among scholars in their interpretation of empirical measures used to operationalize concepts that are central to the premise of routine activity theory. Poor delineation of the key concepts, in turn, leads to inconsistent interpretations. Both limitations undermine routine activity theory’s ability to identify and properly structure the causal mechanisms that create victimization opportunities.
A third limitation is related to what Lynch (1987) referred to as the internal heterogeneity of classes of crime. Expected relationships between key concepts and victimization may vary by type of crime, so variables that correlate positively with one type of victimization may correlate negatively with another. Consider the variable of nonhousehold activity as an example. Studies hypothesize that property victimization is more common among individuals who spend more time away from home (Miethe, Stafford, and Long 1987). But as Finkelhor and Asdigian (1996) explained, a measure of nonhousehold activity applies differently to parental assault because offenders are not strangers but rather most likely are primary caregivers. Whereas one would expect nonhousehold activity to serve as a risk factor for property victimization, it would be considered a protective factor against parental assault. Assuming that adults outside the home provide effective guardianship, nonhousehold activity will be inversely related to this type of victimization. This argument suggests that in specifying models and interpreting findings, researchers need to be prudent when accounting for these crime-specific dynamics.
V. Predictive Validity
Beyond the measurement of key theoretical concepts, the predictive validity of a theory is judged by consistent findings across studies. Having examined the correspondence between concepts and measurement, we turn to a second criterion to assess theories—predictive validity. In this section, we describe the results from studies that have applied routine activity theory to individual, macro, and multi levels of analysis.
A. Individual-Level Studies
The majority of studies testing routine activity theory examine how individuals’ risky lifestyles-routines affect their likelihood of experiencing victimization. Researchers also have explored how individuals’ participation in unstructured peer socializing affects opportunities for criminal offending. Overall, findings have revealed varying degrees of support for routine activity theory when applied to victimization and offending.
(p. 524) 1. Property Victimization
A number of studies of property victimization have offered support for routine activity theory. Cohen, Kluegel, and Land (1981) examined lifestyles associated with personal larceny and burglary victimization. Their results indicated that people residing in rural areas, who were married, and who were employed had significantly lower risks of property victimization, possibly as a function of higher levels of guardianship and lower exposure to would-be offenders. Although Cohen and colleagues’ findings offered some support to the lifestyle-routine activity approach, their conclusions can be seen as tentative because they used proxy measures to operationalize the key concepts.
Miethe, Stafford, and Long (1987) assessed whether a more direct measure of exposure—the frequency of night activity—would be positively related to burglary, household larceny, and auto theft victimization. Supporting their expectations, the results showed that individuals who went out at night more often or whose major activity was performed away from home were more likely to be victimized. Their study, however, examined only exposure, one of the four key concepts of the theory.
Miethe and Meier (1990) conducted a more complete test that included measures of all four concepts of lifestyle-routine activity theory. They reported that individuals who resided in neighborhoods perceived as unsafe, were urban dwellers, had lower levels of home occupancy, engaged in more night leisure activity, and possessed more portable goods were at higher risk of burglary and personal theft victimization. Target attractiveness measures, with the exception of VCR ownership, were unrelated to victimization risk. Despite its comprehensiveness, their study is limited because it fails to explain why specific lifestyles-routines contribute to victimization vulnerability.
Mustaine and Tewksbury (1998) claimed that it is necessary to use more refined measures of lifestyles-routines to better understand the causal processes linking demographic characteristics with criminal victimization. To this end, they examined the effects of multiple specific lifestyles on the risk of larceny victimization. Their analyses revealed that college students who frequently ate out, were members of a student organization/club, smoked marijuana, threatened others, or lived in noisy neighborhoods were significantly more likely to experience larceny. In contrast, students who frequently played tennis or basketball in public places (e.g., city courts), owned a dog, or installed extra locks in their residences were less likely to be victimized. As these more refined measures show, it is not just leaving home but where one goes and what one does that distinguishes between victims and nonvictims.
The results from burglary studies also are supportive of routine activity theory. Tseloni et al. (2004) examined the correlates of burglary victimization across England and Wales, the United States, and the Netherlands. They found that people residing in inner-city areas as well as those with fewer protective measures and lower levels of social guardianship were at higher risk of burglary victimization. Their observations underscore the importance of guardianship and target attractiveness as predictors of burglary—as has also been shown in other studies (Cohen and Cantor 1981; Coupe and Blake 2006; Reynald 2009).
(p. 525) The main findings of this body of research appear to be generalizable across multiple geographical contexts (Fisher and Wilkes 2003; Zhang, Messner, and Liu 2007), across specialized populations such as college and high school students (Mustaine and Tewksbury 1998; Burrow and Apel 2008), and across specific domains such as the workplace (Lynch 1987; Wooldredge, Cullen, and Latessa 1992). With few exceptions (Massey, Krohn, and Bonati 1989), the risk factors for property victimization uncovered are largely consistent with routine activity theory.
2. Violent Victimization
The evidence on the role of lifestyles-routines to explain violent victimization reveals mixed findings. Miethe, Stafford, and Long (1987) reported that people who went out at night more often had higher risks of assault and robbery. Whether their major occupation was performed away from home was not significantly related to victimization. Additionally, the researchers’ measures of lifestyles failed to mediate the effects of demographic variables on victimization. They argued that routine activity theory may not apply to expressive crimes—as it does to instrumental crimes—because these tend to be impulsive in nature, which defies the view of rationally motivated offenders implicit in routine activity theory. Sampson (1987) reported analogous findings in his study of personal violence. He showed that the number of nights per week individuals went out for leisure activities had no effect on the likelihood of rape, simple assault, or aggravated assault once neighborhood context characteristics were taken into account.
Contrary to these findings, it appears that other lifestyles-routines correlate with violent victimization. For example, Miethe and Meier’s (1990) results regarding personal assault comport well with the theory. Individuals who resided in high-crime and unsafe neighborhoods, were urban dwellers, frequently went out at night for leisure, carried cash in public, lived alone, and did not possess any weapons or alarms were more likely to be assault victims. Schreck and Fisher’s (2004) analyses indicated that adolescents who engaged in leisure activities with little supervision—such as those who sneaked out of the home at night—had a higher risk of violent victimization, even after accounting for family context and peer associations. In another study, Burrow and Apel (2008) found that the risk for school assault was higher among students who made long commutes to school, participated in extracurricular activities, skipped classes, and fought at school.
Other lifestyles-routines considered are drug and alcohol use, gang membership, and delinquent lifestyles. Lasley (1989) contended that a drinking lifestyle was directly associated with violent victimization, because individuals who frequently go to bars are more exposed to likely offenders and are less likely to serve as capable guardians while inebriated. Supporting this hypothesis, the data suggested that as individuals engaged in high-exposure drinking routines, their risk of predatory victimization increased significantly. Studies have replicated this finding (p. 526) when examining other forms of violent victimization. Schwartz and Pitts (1995) found that the number of times a woman goes out drinking was a significant predictor of sexual victimization. Other studies have reported drug use as a significant predictor of sexual victimization (Mustaine and Tewksbury 2002; Cass 2007).
Gang membership has been considered as another victimogenic lifestyle. Taylor, Freng, Esbensen, and Peterson (2008) have argued that youths who participate in gangs are at increased risk of violent victimization, due to more proximity and exposure to likely offenders. However, Spano, Freilich and Bolland (2008) noted that it is possible to conceive gang participation as a protective factor, because gang members guard each other against victimization. The evidence largely contests these arguments. Taylor and his colleagues (2008) found that although gang members were more likely to be assaulted and robbed, this effect disappeared once other factors were considered. The effect of gang membership on victimization was fully mediated by self-reported delinquency. Spano, Freilich, and Bolland (2008) also reported no effects of gang membership on victimization. There appears to be little support for gang membership as a dangerous lifestyle by itself. Instead, it is a delinquent lifestyle that places individuals at most risk (see research on victim-offender overlap by Sampson and Lauritsen 1990; Henson et al. 2010).
This body of findings suggests that a few lifestyles are linked to violent victimization. Consistent evidence finds that victimization is significantly higher among individuals who use drugs and alcohol often, and those who engage in antisocial behavior. Although high-exposure lifestyles, such as skipping class or sneaking out of home at night, have been linked to violent victimization, there is mixed evidence on the most used indicator of exposure—going out at night for leisure.
3. Delinquency and Criminal Offending
A growing literature has explored how specific routines provide opportunities for engaging in offending behavior. Osgood and colleagues (1996) hypothesized that individuals who spend more time in unstructured, unsupervised socializing with their peers are exposed to more situational inducements to deviance, which in turn increases delinquency. Supportive of their hypothesis, they found that offending was more prevalent among youths who spent more time in unstructured socializing activities, such as riding a car for fun, visiting with friends, or going to parties. Subsequent research has shown that the positive effect of unstructured socializing on delinquent behavior remains independent of attachment to conventional social agents (Bernburg and Thorlindsson 2001) or to delinquent associates (Haynie and Osgood 2005). Other research has shown that individual offending increases in contexts with larger aggregate levels of unstructured socializing, net of individual risk factors (Osgood and Anderson 2004).
In sum, the evidence on routine activity theory as applied to criminal offending is largely supportive. Multiple studies have shown that, even after considering contextual effects, time spent in unsupervised and unstructured activities is a predictor of delinquency (Anderson and Hughes 2009; Svensson and Oberwittler 2010).
(p. 527) B. Macro-Level Studies
Researchers have tested Cohen and Felson’s macro-level analytical framework by modeling the relationship between changes in social structures and changes in rates of crime and victimization at various levels of aggregation, including face blocks, city blocks, neighborhoods, and census tracts. The accumulated evidence suggests that although the theory has been verified with smaller aggregates, the evidence collectively is characterized by mixed findings.
Thus, Roncek and Maier (1991) hypothesized that the presence of bars and taverns can increase the number of crimes through several mechanisms. First, patrons and businesses are attractive targets, given increased flow of cash and reduced guardianship due to intoxication. Second, bars may attract potential offenders, and the density of strangers may undermine guardianship. Roncek and Maier found a positive relationship between the number of bars and taverns and city-block violent and property crime rates, controlling for crime in surrounding blocks, block size, population density, and socioeconomic composition. Rice and Smith (2002) studied automotive theft at the face-block level using an integrated model of routine activity and social disorganization theories. They found that, with the exception of the number of stores and shops in the block, all of the indicators of routine activity—including number of commercial places, vacant parking lots, multifamily dwellings, average property value—were significant predictors of auto theft. These findings are consistent with those reported by Smith, Frazee, and Davidson (2000) who found that measures of exposure to crime and guardianship were related to street robbery in face blocks.
Bernasco and Luykx (2003) explored the thesis that neighborhoods with higher levels of attractiveness (measured by percentage of home ownership and average real estate values), criminal opportunity (measured by ethnic heterogeneity and residential mobility), and accessibility (measured by proximity to burglars’ homes and to central business district) have higher rates of burglary. Supporting routine activity theory, they reported significant positive coefficients for all six variables.
Studies of cities or SMSAs have produced mixed findings. Messner and Blau (1987) examined the link between aggregate household/nonhousehold activities and serious crime rates. Lending support to routine activity theory, they found that the volume of at-home leisure activities, measured by the rate of television viewing, was negatively related to rates of violent and property crime. The volume of nonhousehold leisure activities (the number of cinemas, entertainment places, and sport establishments) was directly related to crime rates. However, Carroll and Jackson (1983) found that the effect of the household activity ratio on robbery rates was entirely mediated by inequality. Miethe, Hughes, and McDowall’s (1991) study of crime rates in U.S cities also offers contradictory evidence. Particularly, a measure of social guardianship (mean household size) was inversely related to rates of burglary, robbery, and homicide, but no other indicator of routine activities had consistent effects on cross-sectional crime rates or changes in crime rates over time.
(p. 528) As this discussion shows, the macro-level evidence on the empirical validity of routine activity is inconclusive. While studies examining more homogeneous units of analysis—such as face and city blocks—offer support for the theory, other studies show mixed findings or no relationship. These observations resonate with the criticism that tests of routine activity theory at the macro-level are inadequate because aggregate-level data at best poorly capture and most likely cannot capture the spatio-temporal dynamics of situational crime inducements (Eck 1995).
C. Multilevel Studies
Researchers incorporate micro-level and macro-level measures into their analyses by estimating multilevel models. These models statistically control for compositional effects of individual-level variables on the probability of victimization, along with contextual-level effects (see also Wilcox, Gialopsos, and Land in this volume). Although these studies generally use measures of routine activity at the individual level and use social disorganization indicators at the contextual level, the findings offer moderate support for routine activity theory.
Sampson and Wooldredge (1987) published one of the earliest tests of the multilevel opportunity approach. Their analyses showed that both individual characteristics and neighborhood context affect victimization risks. Age of head of household, single occupancy, and the number of hours the home was unoccupied were significantly related to the odds of burglary victimization. Similar to other studies (Sampson 1985; Smith and Jarjoura 1988), there were significant effects at the neighborhood level, showing that households located in communities with higher levels of unemployment, high building density, more single-person households and larger percentage of homes owning a VCR had higher risks of burglary whereas households located in high social cohesion areas had lower risks. Analogous results were reported for personal theft and personal larceny without contact.
Kennedy and Forde (1990) found that measures of an individual’s exposure—going out to bars, sports, work/class—were significantly and directly related to property and violent victimization, even after controlling for contextual variables. Miethe and McDowall (1993) reported that individual and contextual measures affected the likelihood of victimization. Age, living alone, income, and participation in nonhousehold leisure activities were significant predictors of violent victimization. At the city-block level, busy places and poor socioeconomic conditions were significantly linked to violent victimization. Similar findings were found for burglary victimization. Importantly, the researchers found that measures of target attractiveness and guardianship were important covariates of risk among those who resided in more affluent and stable neighborhoods, but their effects were tempered among residents of highly disorganized areas. This study shows that multilevel criminal opportunities affect victimization risk through both main and interaction effects.
Wilcox Rountree, Land, and Miethe (1994) reexamined Miethe and McDowall’s findings to determine whether the use of statistical techniques appropriate for nested data altered the main findings. Compared to Miethe and McDowall’s (p. 529) (1993) findings, Wilcox and colleagues reported some discrepancies for violent victimization, with less support for routine activity at the individual level, but similar findings for burglary victimization. In another study of the multilevel link between guardianship and burglary, Wilcox, Madensen, and Tillyer (2007) found that the effect of individual guardianship measures—such as target hardening and home occupancy—on reducing the risk of burglary victimization was stronger in high guardianship neighborhoods, but was attenuated in low guardianship neighborhoods.
The accumulated evidence suggests that, consistent with a routine activity approach, various lifestyles-routines affect victimization, even after controlling for contextual factors. Multilevel studies have shown main effects consistent with routine activity theory but have also pointed to interactions between individual and contextual measures. Coupled with evidence from college student samples (Fisher et al. 1998) and studies of repeat and multiple victimization (Outlaw, Ruback, and Britt 2002), multilevel studies of victimization show moderate support for routine activity theory.
VI. Conclusions and Implications for Future Research
The purpose of this chapter was to examine the predictive validity of routine activity theory, through the lens of measurement issues and the findings of empirical tests. A comparative review of the research highlights the unique contributions of routine activity theory relative to criminological theories. Its primary theoretical contribution is providing an explanation for how and why lifestyles-routines are associated with the risk of victimization.
The current body of research suggests that routine activity theory has moderate predictive validity when applied to property victimization, criminal offending, and multilevel criminal opportunity. Mixed findings appear in studies of violent victimization, consistent with the criticism that depicting offenders as rational may not fit the impulsive nature of instrumental crimes. It is also possible that consistent findings have not emerged because studies fail to measure target attractiveness processes beyond economic worth. Although research at the macro level is mixed, supportive evidence at the lowest levels of aggregation implies that the situational inducements of crime are better reflected in studies with more homogeneous units of analysis, such as face blocks.
Since most researchers have primarily used cross-sectional designs to test routine activity theory, it has not been possible to rule out effects of prior victimization. For example, Miethe and Meier (1990) found that target hardening measures were significantly and positively associated with victimization, an observation in the opposite (p. 530) direction from their predictions. Prior victimization may also explain why a person adopted such measures, but in the absence of longitudinal data it is impossible to determine the reasons for victims’ vulnerability.
Future research must examine the predictive validity of routine activity using longitudinal data to establish causality and to account for prior victimization effects on lifestyles-routines and vice versa. Additionally, future research needs to incorporate direct measures as well as multiple measures of all four key concepts in simultaneous statistical models. Given the multiplicative nature of the relationships between proximity, exposure, target attractiveness, and guardianship, nonlinear dynamics should be explored. Until researchers better address methodological concerns, in particular the measurement issues of the key concepts, the predictive validity of routine activity theory will remain an open question—yet one certainly deserving of further scientific scrutiny.
Anderson, Amy L., and Lorine A. Hughes. 2009. “Exposure to Situations Conducive to Delinquent Behavior: The Effects of Time Use, Income, and Transportation.” Journal of Research in Crime and Delinquency 46: 5–34.Find this resource:
Bernasco, Wim, and Floor Luykx. 2003. “Effects of Attractiveness, Opportunity and Accessibility to Burglars on Residential Burglary Rates of Urban Neighborhoods.” Criminology 41: 981–1001.Find this resource:
Bernburg, Jon G., and Thorolfur Thorlindsson. 2001. “Routine Activities in Social Context: A Closer Look at the Role of Opportunity in Deviant Behavior.” Justice Quarterly 18: 543–67.Find this resource:
Burrow, John D., and Robert Apel. 2008. “Youth Behavior, School Structure, and Student Risk of Victimization.” Justice Quarterly 25: 349–80.Find this resource:
Carroll, Leo, and Pamela Jackson. 1983. “Inequality, Opportunity, and Crime Rates in Central Cities.” Criminology 21: 178–94.Find this resource:
(p. 531) Cass, Amy I. 2007. “Routine Activities and Sexual Assault: An Analysis of Individual- and School-Level Factors.” Violence and Victims 22: 350–66.Find this resource:
Clarke, Ronald V. 1999. Hot Products: Understanding, Anticipating and Reducing Demand for Stolen Goods. London: Home Office.Find this resource:
Cohen, Lawrence E., and David Cantor. 1981. “Residential Burglary in the United States: Life-Style and Demographic Factors Associated with the Probability of Victimization.” Journal of Research in Crime and Delinquency 18: 113–27.Find this resource:
Cohen, Lawrence E., and Marcus Felson. 1979. “Social Change and Crime Rate Trends: Routine Activity Approach.” American Sociological Review 44: 588–608.Find this resource:
Cohen, Lawrence E., James R. Kluegel, and Kenneth C. Land. 1981. “Social Inequality and Predatory Criminal Victimization: An Exposition and Test of a Formal Theory.” American Sociological Review 46: 505–24.Find this resource:
Coupe, Timothy, and Laurence Blake. 2006. “Daylight and Darkness: Targeting Strategies and the Risks of Being Seen at Residential Burglaries.” Criminology 44: 431–63.Find this resource:
Eck, John E. 1995. “Examining Routine Activity Theory: A Review of Two Books.” Justice Quarterly 12: 783–97.Find this resource:
Felson, Marcus, and Lawrence E. Cohen. 1980. “Human Ecology and Crime: A Routine Activity Approach.” Human Ecology 8: 389–406.Find this resource:
Finkelhor, David, and Nancy L. Asdigian. 1996. “Risk Factors for Youth Victimization: Beyond a Lifestyle/Routine Activities Theory Approach.” Violence and Victims 11: 3–19.Find this resource:
Fisher, Bonnie S., Francis T. Cullen, and Michael G. Turner. 2002. “Being Pursued: Stalking Victimization in a National Study of College Women.” Criminology and Public Policy 1: 257–308.Find this resource:
Fisher, Bonnie S., John J. Sloan, Francis T. Cullen, and Chunmeng Lu. 1998. “Crime in the Ivory Tower: The Level and Sources of Student Victimization.” Criminology 36: 671–710.Find this resource:
Fisher, Bonnie S., and Andrew R. P. Wilkes. 2003. “A Tale of Two Ivory Towers: A Comparative Analysis of Victimization Rates and Risks between University Students in the United States and England.” British Journal of Criminology 43: 526–45.Find this resource:
Gover, Angela. 2004. “Risky Lifestyles and Dating Violence: A Theoretical Test of Violent Victimization.” Journal of Criminal Justice 32: 171–80.Find this resource:
Hawley, Amos. 1950. Human Ecology: A Theory of Community Structure. New York: Ronald Press.Find this resource:
Haynie, Dana L., and D. Wayne Osgood. 2005. “Reconsidering Peers and Delinquency: How Do Peers Matter?” Social Forces 84: 1109–30.Find this resource:
Henson, Billy, Pamela Wilcox, Bradford W. Reyns, and Francis T. Cullen. 2010. “Gender, Adolescent Lifestyles, and Violent Victimization: Implications for Routine Activity Theory.” Victims and Offenders 5: 303–28.Find this resource:
Hindelang, Michael J., Michael R. Gottfredson, and James Garofalo. 1978. Victims of Personal Crime: An Empirical Foundation for a Theory of Personal Victimization. Cambridge, MA: Ballinger.Find this resource:
Hollis-Peel, Meghan, Danielle M. Reynald, Maud van Bavel, Henk Elffers, and Brandon C. Welsh. 2011. “Guardianship for Crime Prevention: A Critical Review of the Literature.” Crime, Law and Social Change 56: 53–70.Find this resource:
Kennedy, Leslie W., and David R. Forde. 1990. “Routine Activities and Crime: An Analysis of Victimization in Canada.” Criminology 28: 137–52.Find this resource:
Lasley, James R. 1989. “Drinking Routines/Lifestyles and Predatory Victimization: A Causal Analysis.” Justice Quarterly 6: 529–42.Find this resource:
(p. 532) Lynch, James P. 1987. “Routine Activity and Victimization at Work.” Journal of Quantitative Criminology 3: 283–300.Find this resource:
Massey, James L., Marvin D. Krohn, and Lisa M. Bonati. 1989. “Property Crime and the Routine Activities of Individuals.” Journal of Research in Crime and Delinquency 26: 378–400.Find this resource:
Meier, Robert F., and Terance D. Miethe. 1993. “Understanding Theories of Criminal Victimization.” In Crime and Justice: A Review of Research, Vol. 17, edited by Michael Tonry. Chicago: University of Chicago Press.Find this resource:
Messner, Steven F., and Judith R. Blau. 1987. “Routine Leisure Activities and Rates of Crime: A Macro-Level Analysis.” Social Forces 65: 1035–53.Find this resource:
Messner, Steven F., Zhou Lu, Lening Zhang, and Jianhong Liu. 2007. “Risks of Criminal Victimization in Contemporary Urban China: An Application of Lifestyle/Routine Activities Theory.” Justice Quarterly 24: 496–522.Find this resource:
Miethe, Terance D., Michael Hughes, and David McDowall. 1991. “Social Change and Crime Rates: An Evaluation of Alternative Theoretical Approaches.” Social Forces 70: 165–87.Find this resource:
Miethe, Terance D., and David McDowall. 1993. “Contextual Effects in Models of Criminal Victimization.” Social Forces 71: 741–59.Find this resource:
Miethe, Terance D., and Robert F. Meier. 1990. “Opportunity, Choice and Criminal Victimization: A Test of a Theoretical Model.” Journal of Research in Crime and Delinquency 27: 243–66.Find this resource:
Miethe, Terance D., Mark C. Stafford, and J. Scott Long. 1987. “Social Differentiation in Criminal Victimization: A Test of Routine Activities/Lifestyles Theories.” American Sociological Review 52: 184–94.Find this resource:
Mustaine, Elizabeth E., and Richard Tewksbury. 1998. “Predicting Risks of Larceny Theft Victimization: A Routine Activity Analysis Using Refined Lifestyle Measures.” Criminology 36: 829–57.Find this resource:
Mustaine, Elizabeth E., and Richard Tewksbury. 1999. “A Routine Activity Theory Explanation for Women’s Stalking Victimization.” Violence Against Women 5: 43–62.Find this resource:
Mustaine, Elizabeth E., and Richard Tewksbury. 2002. “Sexual Assault of College Women: A Feminist Interpretation of a Routine Activities Analysis.” Criminal Justice Review 27: 89–123.Find this resource:
Osgood, D. Wayne, and Amy L. Anderson. 2004. “Unstructured Socializing and Rates of Delinquency.” Criminology 42: 519–49.Find this resource:
Osgood, D. Wayne, Janet K. Wilson, Patrick M. Omalley, Jerald G. Bachman, and Lloyd. D. Johnston. 1996. “Routine Activities and Individual Deviant Behavior.” American Sociological Review 61: 635–55.Find this resource:
Outlaw, Maureen, Barry Ruback, and Chester Britt. 2002. “Repeat and Multiple Victimizations: The Role of Individual and Contextual Factors.” Violence and Victims 17: 187–204.Find this resource:
Pires, Stephen F., and Ronald V. Clarke. Forthcoming. “Are Parrots CRAVED? An Analysis of Parrot Poaching in Mexico.” Journal of Research in Crime and Delinquency.Find this resource:
Pratt, Travis C., and Francis T. Cullen. 2005. “Assessing Macro-Level Predictors and Theories of Crime: A Meta-Analysis.” In Crime and Justice: A Review of Research, Vol. 32, edited by Michael Tonry. Chicago: University of Chicago Press.Find this resource:
Pratt, Travis C., Kristy Holtfreter, and Michael D. Reisig. 2010. “Routine Online Activity and Internet Fraud Targeting: Extending the Generality of Routine Activity Theory.” Journal of Research in Crime and Delinquency 47: 267–96.Find this resource:
(p. 533) Reynald, Danielle M. 2009. “Guardianship in Action: Developing a New Tool for Measurement.” Crime Prevention and Community Safety 11: 1–20.Find this resource:
Reyns, Bradford W., Billy Henson, and Bonnie S. Fisher. 2011. “Being Pursued Online: Applying Cyberlifestyle-Routine Activities Theory to Cyberstalking Victimization.” Criminal Justice and Behavior 38: 1149–69.Find this resource:
Rice, Kennon J., and William R. Smith. 2002. “Socioecological Models of Automotive Theft: Integrating Routine Activity and Social Disorganization Approaches.” Journal of Research in Crime and Delinquency 39: 304–36.Find this resource:
Roncek, Dennis W., and Pamela A. Maier. 1991. “Bars, Blocks and Crimes Revisited: Linking the Theory of Routine Activities to the Empiricism of ‘Hot Spots.’” Criminology 29: 725–53.Find this resource:
Sampson, Robert J. 1985. “Neighborhood and Crime: The Structural Determinants of Personal Victimization.” Journal of Research in Crime and Delinquency 22: 7–40.Find this resource:
Sampson, Robert J. 1987. “Personal Violence by Strangers: An Extension and Test of the Opportunity Model of Predatory Victimization.” Journal of Criminal Law and Criminology 78: 327–56.Find this resource:
Sampson, Robert J., and John D. Wooldredge. 1987. “Linking the Micro- and Macro-Level Dimensions of Lifestyle-Routine Activity and Opportunity Models of Predatory Victimization.” Journal of Quantitative Criminology 3: 371–93.Find this resource:
Sampson, Robert J., and Janet L. Lauritsen. 1990. “Deviant Lifestyles, Proximity to Crime and the Offender-Victim Link in Personal Violence.” Journal of Research in Crime and Delinquency 27: 110–39.Find this resource:
Schreck, Christopher J., and Bonnie S. Fisher. 2004. “Specifying the Influence of Family and Peers on Violent Victimization: Extending Routine Activities and Lifestyles Theories.” Journal of Interpersonal Violence 19: 1021–41.Find this resource:
Schreck, Christopher J., Eric Stewart, and Bonnie S. Fisher. 2006. “Self-Control, Victimization, and Their Influence on Risky Lifestyles: A Longitudinal Analysis Using Panel Data.” Journal of Quantitative Criminology 22: 319–40.Find this resource:
Schwartz, Martin D., and Victoria L. Pitts. 1995. “Exploring a Feminist Routine Activities Approach to Explaining Sexual Assault.” Justice Quarterly 12: 9–31.Find this resource:
Smith, Douglas A., and Roger G. Jarjoura. 1988. “Household Characteristics, Neighborhood Composition and Victimization Risk.” Social Forces 68: 621–40.Find this resource:
Smith, William R., Sharon G. Frazee, and Elizabeth L. Davison. 2000. “Furthering the Integration of Routine Activity and Social Disorganization Theories: Small Units of Analysis and the Study of Street Robbery as a Diffusion Process.” Criminology 38: 489–523.Find this resource:
Spano, Richard, and Steve Nagy. 2005. “Social Guardianship and Social Isolation: An Application and Extension of Lifestyle/Routine Activities Theory to Rural Adolescents.” Rural Sociology 70: 414–37.Find this resource:
Spano, Richard, and Joshua D. Freilich. 2009. “An Assessment of the Empirical Validity and Conceptualization of Individual Level Multivariate Studies of Lifestyle/Routine Activities Theory Published from 1995 to 2005.” Journal of Criminal Justice 37: 305–14.Find this resource:
Spano, Richard, Joshua D. Freilich, and John Bolland. 2008. “Gang Membership, Gun Carrying, and Employment: Applying Routine Activities Theory to Explain Violent Victimization among Inner City, Minority Youth Living in Extreme Poverty.” Justice Quarterly 25: 381–410.Find this resource:
Svensson, Robert, and Dietrich Oberwittler. 2010. “It’s Not the Time They Spend, It’s What They Do: The Interaction between Delinquent Friends and Unstructured Routine (p. 534) Activity on Delinquency: Findings from Two Countries.” Journal of Criminal Justice 38: 1006–14.Find this resource:
Taylor, Terrance J., Adrienne Freng, Finn-Aage Esbensen, and Dana Peterson. 2008. “Youth Gang Membership and Serious Violent Victimization: The Importance of Lifestyles and Routine Activities.” Journal of Interpersonal Violence 23: 1441–64.Find this resource:
Tseloni, Andromachi, Karin Wittebrood, Graham Farrell, and Ken Pease. 2004. “Burglary Victimization in England and Wales, the United States and the Netherlands: A Cross-National Comparative Test of Routine Activities and Lifestyle Theories.” British Journal of Criminology 44: 66–91.Find this resource:
Wilcox Rountree, Pamela, Kenneth C. Land, and Terance D. Miethe. 1994. “Macro-Micro Integration in the Study of Victimization: A Hierarchical Logistic Model Analysis across Seattle Neighborhoods.” Criminology 32: 387–414.Find this resource:
Wilcox Rountree, Pamela, and Kenneth C. Land. 1996. “Burglary Victimization, Perceptions of Crime Risk, and Routine Activities: A Multilevel Analysis across Seattle Neighborhoods and Census Tracts.” Journal of Research in Crime and Delinquency 33: 147–80.Find this resource:
Wilcox, Pamela, Marie Skubak Tillyer, and Bonnie S. Fisher. 2009. “Gendered Opportunity? School-Based Adolescent Victimization.” Journal of Research in Crime and Delinquency 46: 245–69.Find this resource:
Wilcox, Pamela, Kenneth C. Land, and Scott A. Hunt. 2003. Criminal Circumstance: A Dynamic Multicontextual Criminal Opportunity Theory. Hawthorne, NY: Walter de Gruyter.Find this resource:
Wilcox, Pamela, Tamara D. Madensen, and Marie Skubak Tillyer. 2007. “Guardianship in Context: Implications for Burglary Victimization Risk and Prevention.” Criminology 45: 771–803.Find this resource:
Wooldredge, John D., Francis T. Cullen, and Edward J. Latessa. 1992. “Victimization in the Workplace: A Test of Routine Activities Theory.” Justice Quarterly 9: 325–35.Find this resource:
Zhang, Lening, Steven F. Messner, and Jianhong Liu. 2007. “A Multilevel Analysis of the Risk of Household Burglary in the City of Tianjin, China.” British Journal of Criminology 47: 918–37.Find this resource:
(1) . Cohen and Felson (1979) calculated the household activity ratio for each year by adding the number of married, husband-present female labor force participants to the number of non-husband-wife households, and dividing this sum by the total number of households in the United States.
(2) . Although Cohen and Felson (1979) conceived target suitability in the original routine activity theory as a function of the target’s value, inertia, visibility, and accessibility, Cohen, Kluegel, and Land (1981) described target attractiveness in terms of the first two components only. They included the elements of visibility and accessibility under their notion of exposure, which was hypothesized to affect victimization independently of target attractiveness.